Overview

Brought to you by YData

Dataset statistics

Number of variables18
Number of observations3936
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory277.0 B

Variable types

DateTime2
Numeric15
Categorical1

Alerts

Down is highly overall correlated with spHigh correlation
Up is highly overall correlated with spHigh correlation
air_temperature is highly overall correlated with electricity_consumption_Finnish_networks and 2 other fieldsHigh correlation
cloud_amount is highly overall correlated with precipitation_amountHigh correlation
electricity_consumption is highly overall correlated with electricity_consumption_Finnish_networks and 1 other fieldsHigh correlation
electricity_consumption_Finnish_networks is highly overall correlated with air_temperature and 2 other fieldsHigh correlation
electricity_consumption_forecast is highly overall correlated with air_temperature and 2 other fieldsHigh correlation
precipitation_amount is highly overall correlated with cloud_amountHigh correlation
relative_humidity is highly overall correlated with air_temperatureHigh correlation
sp is highly overall correlated with Down and 1 other fieldsHigh correlation
is_public_holiday is highly imbalanced (86.8%) Imbalance
Down_Cap is highly skewed (γ1 = 24.80397633) Skewed
datetime has unique values Unique
electricity_consumption_Finnish_networks has unique values Unique
sp has 113 (2.9%) zeros Zeros
cloud_amount has 57 (1.4%) zeros Zeros
precipitation_amount has 2511 (63.8%) zeros Zeros
Down_Cap has 40 (1.0%) zeros Zeros
Up_Cap has 40 (1.0%) zeros Zeros

Reproduction

Analysis started2025-02-24 14:07:29.507628
Analysis finished2025-02-24 14:07:43.996451
Duration14.49 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

datetime
Date

Unique 

Distinct3936
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size30.9 KiB
Minimum2024-06-20 22:00:00+00:00
Maximum2024-12-01 22:00:00+00:00
Invalid dates0
Invalid dates (%)0.0%
2025-02-24T15:07:44.038996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:44.124390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Up
Real number (ℝ)

High correlation 

Distinct2895
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.7152
Minimum0.1
Maximum678.935
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:44.210554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile19.2275
Q140.53758
median61.514957
Q3122.39666
95-th percentile254.07625
Maximum678.935
Range678.835
Interquartile range (IQR)81.859079

Descriptive statistics

Standard deviation79.991739
Coefficient of variation (CV)0.87217538
Kurtosis5.5070533
Mean91.7152
Median Absolute Deviation (MAD)28.114166
Skewness2.0866939
Sum360991.03
Variance6398.6784
MonotonicityNot monotonic
2025-02-24T15:07:44.297901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.79999924 14
 
0.4%
44.1906929 13
 
0.3%
17.59000015 13
 
0.3%
139.9400024 12
 
0.3%
74.96250153 8
 
0.2%
40 8
 
0.2%
116.3799973 7
 
0.2%
133.0200043 7
 
0.2%
220.6666718 7
 
0.2%
116.753334 7
 
0.2%
Other values (2885) 3840
97.6%
ValueCountFrequency (%)
0.1000000015 2
0.1%
0.1350000054 1
 
< 0.1%
0.2400000095 1
 
< 0.1%
0.4900000095 1
 
< 0.1%
0.7050000429 1
 
< 0.1%
0.8299999833 1
 
< 0.1%
1 4
0.1%
1.5 1
 
< 0.1%
1.553333282 1
 
< 0.1%
2.091249943 1
 
< 0.1%
ValueCountFrequency (%)
678.9349976 1
 
< 0.1%
599.6650391 1
 
< 0.1%
545.9799805 1
 
< 0.1%
542.6966553 1
 
< 0.1%
513.7199707 1
 
< 0.1%
512.3449707 1
 
< 0.1%
507.9966736 1
 
< 0.1%
500 1
 
< 0.1%
478.664978 1
 
< 0.1%
472.1699829 4
0.1%

Down
Real number (ℝ)

High correlation 

Distinct3386
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-13.077242
Minimum-262.6084
Maximum416.67001
Zeros4
Zeros (%)0.1%
Negative3075
Negative (%)78.1%
Memory size30.9 KiB
2025-02-24T15:07:44.384024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-262.6084
5-th percentile-48.750417
Q1-27.785061
median-16.67625
Q3-3.2057947
95-th percentile35.468125
Maximum416.67001
Range679.27841
Interquartile range (IQR)24.579267

Descriptive statistics

Standard deviation28.104417
Coefficient of variation (CV)-2.1491088
Kurtosis25.049643
Mean-13.077242
Median Absolute Deviation (MAD)12.104166
Skewness1.8779094
Sum-51472.026
Variance789.85827
MonotonicityNot monotonic
2025-02-24T15:07:44.579215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-50 32
 
0.8%
-10 25
 
0.6%
-5 23
 
0.6%
-20 20
 
0.5%
-27.2236557 13
 
0.3%
-51 12
 
0.3%
-30 11
 
0.3%
-30.06000137 11
 
0.3%
50 10
 
0.3%
15.27000046 8
 
0.2%
Other values (3376) 3771
95.8%
ValueCountFrequency (%)
-262.6083984 1
< 0.1%
-237.6840363 1
< 0.1%
-193.8249969 1
< 0.1%
-157.0825043 1
< 0.1%
-154.6350098 1
< 0.1%
-124.3500137 1
< 0.1%
-123.040863 1
< 0.1%
-116.840004 1
< 0.1%
-115.9404449 1
< 0.1%
-113.2881317 1
< 0.1%
ValueCountFrequency (%)
416.6700134 1
< 0.1%
254.7100067 1
< 0.1%
251.5500031 2
0.1%
167.706665 1
< 0.1%
162.7550049 1
< 0.1%
154.8200073 1
< 0.1%
131.4149933 1
< 0.1%
126.6033325 2
0.1%
116.8199997 1
< 0.1%
111.3424988 1
< 0.1%

sp
Real number (ℝ)

High correlation  Zeros 

Distinct2604
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.807683
Minimum-20.01
Maximum500.08
Zeros113
Zeros (%)2.9%
Negative489
Negative (%)12.4%
Memory size30.9 KiB
2025-02-24T15:07:44.662387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-20.01
5-th percentile-1
Q12.9
median16.86
Q335.01
95-th percentile140.02
Maximum500.08
Range520.09
Interquartile range (IQR)32.11

Descriptive statistics

Standard deviation51.58817
Coefficient of variation (CV)1.5724417
Kurtosis15.656608
Mean32.807683
Median Absolute Deviation (MAD)14.8
Skewness3.2677802
Sum129131.04
Variance2661.3393
MonotonicityNot monotonic
2025-02-24T15:07:44.747589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 113
 
2.9%
-0.01 59
 
1.5%
0.01 50
 
1.3%
-0.81 18
 
0.5%
-0.8 17
 
0.4%
-0.11 16
 
0.4%
-0.1 15
 
0.4%
-0.02 14
 
0.4%
-1 13
 
0.3%
-0.59 11
 
0.3%
Other values (2594) 3610
91.7%
ValueCountFrequency (%)
-20.01 1
< 0.1%
-19.9 1
< 0.1%
-19.83 1
< 0.1%
-15.5 1
< 0.1%
-15.02 1
< 0.1%
-15 2
0.1%
-13.49 1
< 0.1%
-12.2 2
0.1%
-12.04 1
< 0.1%
-11.75 1
< 0.1%
ValueCountFrequency (%)
500.08 1
< 0.1%
499.93 1
< 0.1%
498.97 1
< 0.1%
484 1
< 0.1%
476.81 1
< 0.1%
421.5 1
< 0.1%
400.08 1
< 0.1%
393.29 1
< 0.1%
357.12 1
< 0.1%
348.73 1
< 0.1%

cloud_amount
Real number (ℝ)

High correlation  Zeros 

Distinct1510
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5129666
Minimum0
Maximum8.2666667
Zeros57
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:44.842133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.37777778
Q12.2888889
median4.8666667
Q36.7555556
95-th percentile7.9166667
Maximum8.2666667
Range8.2666667
Interquartile range (IQR)4.4666667

Descriptive statistics

Standard deviation2.5046166
Coefficient of variation (CV)0.5549823
Kurtosis-1.2405284
Mean4.5129666
Median Absolute Deviation (MAD)2.1333333
Skewness-0.2724944
Sum17763.037
Variance6.2731043
MonotonicityNot monotonic
2025-02-24T15:07:44.926962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 107
 
2.7%
0 57
 
1.4%
3.744444444 28
 
0.7%
7 16
 
0.4%
0.9888888889 16
 
0.4%
7.5 14
 
0.4%
6.911111111 12
 
0.3%
7.833333254 11
 
0.3%
2.8 11
 
0.3%
7.666666746 11
 
0.3%
Other values (1500) 3653
92.8%
ValueCountFrequency (%)
0 57
1.4%
0.01111111111 9
 
0.2%
0.02222222222 3
 
0.1%
0.03333333333 5
 
0.1%
0.04444444444 1
 
< 0.1%
0.05555555556 4
 
0.1%
0.06666666667 4
 
0.1%
0.07777777778 5
 
0.1%
0.08333333582 4
 
0.1%
0.08888888889 3
 
0.1%
ValueCountFrequency (%)
8.26666673 1
< 0.1%
8.255555566 1
< 0.1%
8.222222169 1
< 0.1%
8.199999968 1
< 0.1%
8.166666698 1
< 0.1%
8.144444434 1
< 0.1%
8.111111132 1
< 0.1%
8.1 1
< 0.1%
8.088888899 1
< 0.1%
8.088888889 1
< 0.1%

wind_speed
Real number (ℝ)

Distinct3151
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3597199
Minimum0.88333333
Maximum10.141667
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:45.010038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.88333333
5-th percentile1.5244444
Q12.3286111
median3.1177778
Q34.0953333
95-th percentile6.14
Maximum10.141667
Range9.2583336
Interquartile range (IQR)1.7667222

Descriptive statistics

Standard deviation1.407906
Coefficient of variation (CV)0.41905459
Kurtosis0.95117797
Mean3.3597199
Median Absolute Deviation (MAD)0.86622222
Skewness0.97794036
Sum13223.857
Variance1.9821994
MonotonicityNot monotonic
2025-02-24T15:07:45.094144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.433333397 84
 
2.1%
3.442222222 26
 
0.7%
2.898888889 6
 
0.2%
3.107777778 5
 
0.1%
2.007777778 4
 
0.1%
2.557777778 4
 
0.1%
3.286666667 4
 
0.1%
2.351111111 4
 
0.1%
4.28 4
 
0.1%
2.635555556 4
 
0.1%
Other values (3141) 3791
96.3%
ValueCountFrequency (%)
0.8833333254 1
< 0.1%
0.9333333333 1
< 0.1%
0.9811111111 1
< 0.1%
1.008333325 2
0.1%
1.037777778 1
< 0.1%
1.041111111 1
< 0.1%
1.07 1
< 0.1%
1.078888889 2
0.1%
1.087777778 1
< 0.1%
1.098888889 1
< 0.1%
ValueCountFrequency (%)
10.14166689 1
< 0.1%
9.416666985 1
< 0.1%
8.741666794 1
< 0.1%
8.541666508 1
< 0.1%
8.466666698 1
< 0.1%
8.358333588 1
< 0.1%
8.341666698 1
< 0.1%
8.304444444 1
< 0.1%
8.233333588 1
< 0.1%
8.225000381 1
< 0.1%

precipitation_amount
Real number (ℝ)

High correlation  Zeros 

Distinct374
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.091422764
Minimum0
Maximum3.6933333
Zeros2511
Zeros (%)63.8%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:45.179239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.04
95-th percentile0.49333333
Maximum3.6933333
Range3.6933333
Interquartile range (IQR)0.04

Descriptive statistics

Standard deviation0.26067723
Coefficient of variation (CV)2.8513383
Kurtosis52.572364
Mean0.091422764
Median Absolute Deviation (MAD)0
Skewness6.0077138
Sum359.84
Variance0.067952616
MonotonicityNot monotonic
2025-02-24T15:07:45.265657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2511
63.8%
0.01333333333 86
 
2.2%
0.400000006 84
 
2.1%
0.006666666667 68
 
1.7%
0.02 62
 
1.6%
0.01333333353 53
 
1.3%
0.04 49
 
1.2%
0.02666666667 37
 
0.9%
0.08 29
 
0.7%
0.05333333333 28
 
0.7%
Other values (364) 929
 
23.6%
ValueCountFrequency (%)
0 2511
63.8%
0.006666666667 68
 
1.7%
0.006666666766 23
 
0.6%
0.01333333333 86
 
2.2%
0.01333333353 53
 
1.3%
0.02 62
 
1.6%
0.0200000003 18
 
0.5%
0.02000000079 2
 
0.1%
0.02666666667 37
 
0.9%
0.02666666706 12
 
0.3%
ValueCountFrequency (%)
3.693333333 1
< 0.1%
3.62 1
< 0.1%
3.22 1
< 0.1%
3.04 1
< 0.1%
2.96 1
< 0.1%
2.949999928 1
< 0.1%
2.78 1
< 0.1%
2.753333333 1
< 0.1%
2.406666667 1
< 0.1%
2.333333333 1
< 0.1%

pressure
Real number (ℝ)

Distinct3677
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1012.0582
Minimum977.95334
Maximum1033.0889
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:45.349999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum977.95334
5-th percentile993.67832
Q11005.7836
median1013.14
Q31018.7687
95-th percentile1028.2683
Maximum1033.0889
Range55.135563
Interquartile range (IQR)12.985137

Descriptive statistics

Standard deviation10.701501
Coefficient of variation (CV)0.010573998
Kurtosis0.71143581
Mean1012.0582
Median Absolute Deviation (MAD)6.3544444
Skewness-0.67939316
Sum3983461.1
Variance114.52213
MonotonicityNot monotonic
2025-02-24T15:07:45.540533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
997.0333252 84
 
2.1%
1023.167778 25
 
0.6%
1013.91 3
 
0.1%
1011.68 3
 
0.1%
1021.891663 3
 
0.1%
1030.531111 3
 
0.1%
1016.678889 3
 
0.1%
1011.165556 2
 
0.1%
1028.206667 2
 
0.1%
1015.024444 2
 
0.1%
Other values (3667) 3806
96.7%
ValueCountFrequency (%)
977.9533366 1
< 0.1%
977.9988851 1
< 0.1%
978.0266683 1
< 0.1%
978.0922282 1
< 0.1%
978.093335 1
< 0.1%
978.1233317 1
< 0.1%
978.1851115 1
< 0.1%
978.2366659 1
< 0.1%
978.2388916 1
< 0.1%
978.3222209 1
< 0.1%
ValueCountFrequency (%)
1033.0889 1
< 0.1%
1033.02111 1
< 0.1%
1032.938883 1
< 0.1%
1032.8111 1
< 0.1%
1032.703337 1
< 0.1%
1032.69445 1
< 0.1%
1032.598885 1
< 0.1%
1032.592212 1
< 0.1%
1032.578882 1
< 0.1%
1032.556657 1
< 0.1%

air_temperature
Real number (ℝ)

High correlation 

Distinct3603
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.156078
Minimum-5.2922223
Maximum28.297778
Zeros0
Zeros (%)0.0%
Negative171
Negative (%)4.3%
Memory size30.9 KiB
2025-02-24T15:07:45.646844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5.2922223
5-th percentile0.40444446
Q15.9740277
median13.56
Q317.6375
95-th percentile22.201111
Maximum28.297778
Range33.59
Interquartile range (IQR)11.663472

Descriptive statistics

Standard deviation7.0270032
Coefficient of variation (CV)0.57806501
Kurtosis-0.87638484
Mean12.156078
Median Absolute Deviation (MAD)5.1522222
Skewness-0.29298899
Sum47846.322
Variance49.378775
MonotonicityNot monotonic
2025-02-24T15:07:45.733413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.083333373 85
 
2.2%
8.897777778 25
 
0.6%
16.96666667 4
 
0.1%
17.71555556 3
 
0.1%
10.5666666 3
 
0.1%
18.53222222 3
 
0.1%
6.451111111 3
 
0.1%
15.12111111 3
 
0.1%
19.25555556 3
 
0.1%
17.15444444 3
 
0.1%
Other values (3593) 3801
96.6%
ValueCountFrequency (%)
-5.292222261 1
< 0.1%
-5.106666712 1
< 0.1%
-4.973333327 1
< 0.1%
-4.964444478 1
< 0.1%
-4.951111118 1
< 0.1%
-4.906666629 1
< 0.1%
-4.862222242 1
< 0.1%
-4.846666622 1
< 0.1%
-4.831111129 1
< 0.1%
-4.814444423 1
< 0.1%
ValueCountFrequency (%)
28.29777778 1
< 0.1%
28.15333333 1
< 0.1%
27.88555556 1
< 0.1%
27.80555556 1
< 0.1%
27.52222222 1
< 0.1%
27.37888889 1
< 0.1%
27.05333333 1
< 0.1%
26.85777778 1
< 0.1%
26.26444444 1
< 0.1%
26.25777778 1
< 0.1%

relative_humidity
Real number (ℝ)

High correlation 

Distinct2976
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.510166
Minimum40.322222
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:45.820273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40.322222
5-th percentile54.041667
Q175.630556
median86.7
Q393.133333
95-th percentile97.586111
Maximum100
Range59.677778
Interquartile range (IQR)17.502777

Descriptive statistics

Standard deviation13.512177
Coefficient of variation (CV)0.16376379
Kurtosis0.21463502
Mean82.510166
Median Absolute Deviation (MAD)7.8555556
Skewness-1.0225235
Sum324760.01
Variance182.57894
MonotonicityNot monotonic
2025-02-24T15:07:45.904792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98 85
 
2.2%
88.43333333 25
 
0.6%
99.5 6
 
0.2%
90 5
 
0.1%
96.75555556 5
 
0.1%
87.9 5
 
0.1%
88.8 5
 
0.1%
94.44444444 5
 
0.1%
88.33333333 5
 
0.1%
94.87777778 5
 
0.1%
Other values (2966) 3785
96.2%
ValueCountFrequency (%)
40.32222222 1
< 0.1%
40.76666667 1
< 0.1%
40.98444444 1
< 0.1%
41.15555556 1
< 0.1%
41.24 1
< 0.1%
41.71111111 1
< 0.1%
41.81111111 1
< 0.1%
41.91111111 1
< 0.1%
42.03333333 1
< 0.1%
42.07777778 1
< 0.1%
ValueCountFrequency (%)
100 2
 
0.1%
99.83333206 1
 
< 0.1%
99.75 1
 
< 0.1%
99.58333206 3
0.1%
99.5 6
0.2%
99.41666794 1
 
< 0.1%
99.34444444 1
 
< 0.1%
99.33333333 1
 
< 0.1%
99.13333333 1
 
< 0.1%
99.08333206 2
 
0.1%

wind_direction
Real number (ℝ)

Distinct3652
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean194.26159
Minimum48.666667
Maximum328.76667
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:45.985417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48.666667
5-th percentile85.477778
Q1150.38611
median202.20833
Q3239.00278
95-th percentile281.69722
Maximum328.76667
Range280.1
Interquartile range (IQR)88.616666

Descriptive statistics

Standard deviation59.137319
Coefficient of variation (CV)0.30442106
Kurtosis-0.61362126
Mean194.26159
Median Absolute Deviation (MAD)44.058334
Skewness-0.34677474
Sum764613.61
Variance3497.2225
MonotonicityNot monotonic
2025-02-24T15:07:46.069690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
62.74999809 84
 
2.1%
192.8777778 25
 
0.6%
272.9444444 3
 
0.1%
258.8333333 3
 
0.1%
236.8777778 3
 
0.1%
236 3
 
0.1%
284 3
 
0.1%
214.6222222 3
 
0.1%
189.9444444 3
 
0.1%
229.2333333 2
 
0.1%
Other values (3642) 3804
96.6%
ValueCountFrequency (%)
48.66666667 1
< 0.1%
48.74444444 1
< 0.1%
50.43333333 1
< 0.1%
51.16666603 1
< 0.1%
51.42222222 1
< 0.1%
53.83333397 1
< 0.1%
54.23333333 1
< 0.1%
54.67777778 1
< 0.1%
54.7 1
< 0.1%
56.96666667 1
< 0.1%
ValueCountFrequency (%)
328.7666667 1
< 0.1%
325.5333333 1
< 0.1%
323.7 1
< 0.1%
323.0555556 1
< 0.1%
322.0333333 1
< 0.1%
320.7777778 1
< 0.1%
320.5333333 1
< 0.1%
320.0888889 1
< 0.1%
318.7555556 1
< 0.1%
318.6333333 1
< 0.1%

date
Date

Distinct164
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size30.9 KiB
Minimum2024-06-21 00:00:00
Maximum2024-12-01 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-02-24T15:07:46.151461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:46.235494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Down_Cap
Real number (ℝ)

Skewed  Zeros 

Distinct976
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.687421
Minimum0
Maximum1837.22
Zeros40
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:46.318925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.93
Q110.83
median15
Q322.18
95-th percentile38.185
Maximum1837.22
Range1837.22
Interquartile range (IQR)11.35

Descriptive statistics

Standard deviation69.847997
Coefficient of variation (CV)3.3763511
Kurtosis626.81135
Mean20.687421
Median Absolute Deviation (MAD)5
Skewness24.803976
Sum81425.69
Variance4878.7426
MonotonicityNot monotonic
2025-02-24T15:07:46.406948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 146
 
3.7%
10 121
 
3.1%
20 85
 
2.2%
14.54 83
 
2.1%
12 82
 
2.1%
14 71
 
1.8%
10.72 66
 
1.7%
11.56 65
 
1.7%
13.96 53
 
1.3%
9 53
 
1.3%
Other values (966) 3111
79.0%
ValueCountFrequency (%)
0 40
1.0%
4.67 6
 
0.2%
4.97 1
 
< 0.1%
5 11
 
0.3%
5.05 1
 
< 0.1%
5.26 4
 
0.1%
5.28 3
 
0.1%
5.36 12
 
0.3%
5.4 9
 
0.2%
5.5 11
 
0.3%
ValueCountFrequency (%)
1837.22 1
 
< 0.1%
1836.61 1
 
< 0.1%
1787.99 1
 
< 0.1%
1787.98 1
 
< 0.1%
1787.42 1
 
< 0.1%
1696.31 1
 
< 0.1%
72.94 1
 
< 0.1%
72.74 1
 
< 0.1%
68 4
0.1%
67.58 1
 
< 0.1%

Up_Cap
Real number (ℝ)

Zeros 

Distinct965
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.014029
Minimum0
Maximum286.65
Zeros40
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:46.494436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q111.16
median15
Q320.355
95-th percentile47.0325
Maximum286.65
Range286.65
Interquartile range (IQR)9.195

Descriptive statistics

Standard deviation20.689134
Coefficient of variation (CV)1.0337316
Kurtosis44.350635
Mean20.014029
Median Absolute Deviation (MAD)4.06
Skewness5.6463726
Sum78775.22
Variance428.04027
MonotonicityNot monotonic
2025-02-24T15:07:46.580490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 169
 
4.3%
12 122
 
3.1%
20 89
 
2.3%
18 81
 
2.1%
15 80
 
2.0%
16 69
 
1.8%
11.16 62
 
1.6%
14 59
 
1.5%
11 57
 
1.4%
13 54
 
1.4%
Other values (955) 3094
78.6%
ValueCountFrequency (%)
0 40
1.0%
3.01 11
 
0.3%
4.91 13
 
0.3%
5.5 10
 
0.3%
6 2
 
0.1%
6.01 1
 
< 0.1%
6.09 5
 
0.1%
6.3 1
 
< 0.1%
6.32 5
 
0.1%
6.46 1
 
< 0.1%
ValueCountFrequency (%)
286.65 1
< 0.1%
286.56 1
< 0.1%
277 1
< 0.1%
221.55 1
< 0.1%
217 1
< 0.1%
199.15 1
< 0.1%
192.61 1
< 0.1%
191.49 1
< 0.1%
191 1
< 0.1%
188.81 1
< 0.1%

is_public_holiday
Categorical

Imbalance 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size223.1 KiB
0
3864 
1
 
72

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3936
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 3864
98.2%
1 72
 
1.8%

Length

2025-02-24T15:07:46.656986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-24T15:07:46.715350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3864
98.2%
1 72
 
1.8%

Most occurring characters

ValueCountFrequency (%)
0 3864
98.2%
1 72
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3936
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3864
98.2%
1 72
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3936
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3864
98.2%
1 72
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3936
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3864
98.2%
1 72
 
1.8%

electricity_consumption
Real number (ℝ)

High correlation 

Distinct3930
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33166.28
Minimum15470.67
Maximum46567.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:46.781913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15470.67
5-th percentile26633.307
Q130072.077
median33048.41
Q335548.735
95-th percentile41341.075
Maximum46567.5
Range31096.83
Interquartile range (IQR)5476.6575

Descriptive statistics

Standard deviation4389.8869
Coefficient of variation (CV)0.13235994
Kurtosis0.042269516
Mean33166.28
Median Absolute Deviation (MAD)2731.995
Skewness0.30025107
Sum1.3054248 × 108
Variance19271107
MonotonicityNot monotonic
2025-02-24T15:07:46.996085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30526.81 2
 
0.1%
32230.1 2
 
0.1%
34595.62 2
 
0.1%
41162.2 2
 
0.1%
32977.01 2
 
0.1%
34430.22 2
 
0.1%
25735.78 1
 
< 0.1%
38228.89 1
 
< 0.1%
39334.83 1
 
< 0.1%
39031.08 1
 
< 0.1%
Other values (3920) 3920
99.6%
ValueCountFrequency (%)
15470.67 1
< 0.1%
16010.49 1
< 0.1%
16891.72 1
< 0.1%
17150.43 1
< 0.1%
17425.12 1
< 0.1%
19316.03 1
< 0.1%
20914.8 1
< 0.1%
22019.79 1
< 0.1%
22241.77 1
< 0.1%
22370.24 1
< 0.1%
ValueCountFrequency (%)
46567.5 1
< 0.1%
46044.2 1
< 0.1%
45846.1 1
< 0.1%
45644.6 1
< 0.1%
45591.9 1
< 0.1%
45536 1
< 0.1%
45371.1 1
< 0.1%
45293 1
< 0.1%
45265.7 1
< 0.1%
45262.5 1
< 0.1%

electricity_consumption_Finnish_networks
Real number (ℝ)

High correlation  Unique 

Distinct3936
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4879402.2
Minimum3008976.4
Maximum7760226.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:47.081086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3008976.4
5-th percentile3400385.7
Q14182705.4
median4784604.4
Q35492959.4
95-th percentile6734019.4
Maximum7760226.9
Range4751250.5
Interquartile range (IQR)1310254

Descriptive statistics

Standard deviation985587.58
Coefficient of variation (CV)0.20198941
Kurtosis-0.32459241
Mean4879402.2
Median Absolute Deviation (MAD)648422.29
Skewness0.45374997
Sum1.9205327 × 1010
Variance9.7138288 × 1011
MonotonicityNot monotonic
2025-02-24T15:07:47.167469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3617520.07 1
 
< 0.1%
5286588.097 1
 
< 0.1%
4751132.938 1
 
< 0.1%
4660466.044 1
 
< 0.1%
4608849.403 1
 
< 0.1%
4639053.227 1
 
< 0.1%
4866747.978 1
 
< 0.1%
5547731.265 1
 
< 0.1%
5984298.083 1
 
< 0.1%
6106104.89 1
 
< 0.1%
Other values (3926) 3926
99.7%
ValueCountFrequency (%)
3008976.433 1
< 0.1%
3034028.607 1
< 0.1%
3034987.924 1
< 0.1%
3041905.342 1
< 0.1%
3042845.103 1
< 0.1%
3045475.584 1
< 0.1%
3045565.154 1
< 0.1%
3054461.381 1
< 0.1%
3055197.043 1
< 0.1%
3065281.979 1
< 0.1%
ValueCountFrequency (%)
7760226.92 1
< 0.1%
7700325.528 1
< 0.1%
7672583.412 1
< 0.1%
7668693.091 1
< 0.1%
7590150.393 1
< 0.1%
7571957.201 1
< 0.1%
7570443.851 1
< 0.1%
7545793.218 1
< 0.1%
7542198.539 1
< 0.1%
7522464.017 1
< 0.1%

electricity_consumption_forecast
Real number (ℝ)

High correlation 

Distinct3871
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33786.902
Minimum23816.1
Maximum44358.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2025-02-24T15:07:47.249851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23816.1
5-th percentile27289.6
Q130913.925
median33524.7
Q336345.425
95-th percentile41306.225
Maximum44358.7
Range20542.6
Interquartile range (IQR)5431.5

Descriptive statistics

Standard deviation4117.8521
Coefficient of variation (CV)0.12187717
Kurtosis-0.4961206
Mean33786.902
Median Absolute Deviation (MAD)2681.5
Skewness0.24802953
Sum1.3298525 × 108
Variance16956706
MonotonicityNot monotonic
2025-02-24T15:07:47.331369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33311.4 3
 
0.1%
34215.9 3
 
0.1%
35584.6 2
 
0.1%
31205.5 2
 
0.1%
35327.6 2
 
0.1%
32777.5 2
 
0.1%
36788.6 2
 
0.1%
34735.3 2
 
0.1%
27852.2 2
 
0.1%
29946.6 2
 
0.1%
Other values (3861) 3914
99.4%
ValueCountFrequency (%)
23816.1 1
< 0.1%
23888.3 1
< 0.1%
23940.6 1
< 0.1%
23990.7 1
< 0.1%
24239.5 1
< 0.1%
24290.3 1
< 0.1%
24346.5 1
< 0.1%
24555.2 1
< 0.1%
24590.6 1
< 0.1%
24624.5 1
< 0.1%
ValueCountFrequency (%)
44358.7 1
< 0.1%
44215.1 1
< 0.1%
44112.3 1
< 0.1%
43839.8 1
< 0.1%
43680.7 1
< 0.1%
43665.6 1
< 0.1%
43659 1
< 0.1%
43658.5 1
< 0.1%
43557.1 1
< 0.1%
43530.7 1
< 0.1%

Interactions

2025-02-24T15:07:42.860711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:29.850057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.828534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.742179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.620140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.629308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.487158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.479374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.375853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.381210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.276994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.157666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.063247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.059120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.970654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.920924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:29.930374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.890425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.801012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.679842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.687368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.560938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.550908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.441006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.444589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.335525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.220412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.125490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.122658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.030998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.980535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.006357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.948230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.864452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.735573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.744269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.622428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.615794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.500627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.504203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.396256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.280363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.184432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.184182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.091172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.037341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.080747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.005884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.922010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.789821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.797978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.681532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.672196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.559055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.561862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.452670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.339083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.240761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.241795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.148725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.093505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.150860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.060761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.977678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.844078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.850118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.739809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.728882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.619194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.617970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.509439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.395541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.294867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.299496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.204861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.149132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.208391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.115441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.031200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.896103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.902784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.796870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.783004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.674354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.674038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.563456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.454961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.350066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.356546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.259178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.211071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.271208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.180989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.091335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.957406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.970867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.861462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.844241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.739045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.738258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.627064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.519498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.413903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.422789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.320681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.270158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.329596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.238829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.150155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.013216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.027719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.921565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.902243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.797161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.796525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.689245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.579816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.472996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.483015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.381561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.328336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.396985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.299113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.207507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.071466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.084687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.983633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.960855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.856325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.857795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.747493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.639758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.533896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.544544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.443205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.390369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.460285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.359085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.266636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.129270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.143999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.045152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.021289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.916472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.916278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.807913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.701471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.595547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.606975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.504395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.449060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.521179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.431579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.322427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.184993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.199068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.106911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.077507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.976227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.975296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.863575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.761301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.653004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.667259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.561242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.511571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.586199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.493661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.383485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.401072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.258187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.170869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.142550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.036770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.037222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.925541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.821940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.714455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.730075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.624120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.569952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.647635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.553659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.445260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.458374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.315452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.232263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.200634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.096284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.097951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.982811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.882642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.774920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.792346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.683949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.629928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.709499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.627251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.506191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.517728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.373254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.294916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.260461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.265228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.159921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.043500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.945181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.944287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.852923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.743829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:43.688813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:30.770926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:31.685894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:32.563710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:33.572373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:34.431367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:35.355860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:36.318820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:37.323809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:38.219109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:39.100779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:40.005001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.001933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:41.911491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-02-24T15:07:42.803599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2025-02-24T15:07:47.395214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
DownDown_CapUpUp_Capair_temperaturecloud_amountelectricity_consumptionelectricity_consumption_Finnish_networkselectricity_consumption_forecastis_public_holidayprecipitation_amountpressurerelative_humidityspwind_directionwind_speed
Down1.000-0.4890.3900.146-0.3350.1710.2090.3760.3290.0390.0080.1890.1720.6080.065-0.198
Down_Cap-0.4891.000-0.1540.0750.225-0.122-0.115-0.257-0.2150.000-0.028-0.110-0.096-0.496-0.0270.187
Up0.390-0.1541.0000.331-0.1450.0370.0870.1970.1800.0990.0330.1840.0750.512-0.017-0.215
Up_Cap0.1460.0750.3311.000-0.0280.0560.2730.3330.3320.0210.0230.152-0.0540.2910.0180.011
air_temperature-0.3350.225-0.145-0.0281.000-0.387-0.315-0.567-0.5070.091-0.0900.003-0.655-0.145-0.1240.022
cloud_amount0.171-0.1220.0370.056-0.3871.0000.2550.3390.3570.1430.542-0.3310.4850.085-0.1290.190
electricity_consumption0.209-0.1150.0870.273-0.3150.2551.0000.7680.7690.1840.115-0.0430.0100.1380.0250.366
electricity_consumption_Finnish_networks0.376-0.2570.1970.333-0.5670.3390.7681.0000.9670.1480.107-0.0090.1480.3130.0780.316
electricity_consumption_forecast0.329-0.2150.1800.332-0.5070.3570.7690.9671.0000.2450.128-0.0310.1250.2640.0750.365
is_public_holiday0.0390.0000.0990.0210.0910.1430.1840.1480.2451.0000.1410.1650.2440.0250.2540.057
precipitation_amount0.008-0.0280.0330.023-0.0900.5420.1150.1070.1280.1411.000-0.4000.240-0.016-0.2120.203
pressure0.189-0.1100.1840.1520.003-0.331-0.043-0.009-0.0310.165-0.4001.0000.0010.2290.079-0.351
relative_humidity0.172-0.0960.075-0.054-0.6550.4850.0100.1480.1250.2440.2400.0011.0000.061-0.095-0.330
sp0.608-0.4960.5120.291-0.1450.0850.1380.3130.2640.025-0.0160.2290.0611.0000.052-0.421
wind_direction0.065-0.027-0.0170.018-0.124-0.1290.0250.0780.0750.254-0.2120.079-0.0950.0521.0000.126
wind_speed-0.1980.187-0.2150.0110.0220.1900.3660.3160.3650.0570.203-0.351-0.330-0.4210.1261.000

Missing values

2025-02-24T15:07:43.778127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2025-02-24T15:07:43.928323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

datetimeUpDownspcloud_amountwind_speedprecipitation_amountpressureair_temperaturerelative_humiditywind_directiondateDown_CapUp_Capis_public_holidayelectricity_consumptionelectricity_consumption_Finnish_networkselectricity_consumption_forecast
02024-06-20 22:00:00+00:0031.416588-30.060369-2.001.8111112.3533330.01006.77444411.57333384.877778249.4333332024-06-2123.829.80125735.783617520.07026816.5
12024-06-20 23:00:00+00:0031.416588-36.460079-2.431.8111112.3111110.01006.78444410.88000086.966667246.7888892024-06-210.000.00125082.633447580.36826178.8
22024-06-21 00:00:00+00:0031.416588-17.130116-5.011.5666672.2488890.01006.78111110.56333386.144444253.9777782024-06-210.000.00124950.973328815.37225513.2
32024-06-21 01:00:00+00:0031.416588-17.130116-6.582.1333332.2788890.01006.75000010.50555685.588889242.0555562024-06-210.000.00124850.313248613.63225324.4
42024-06-21 02:00:00+00:0031.416588-17.130116-2.513.1111112.3566670.01006.84888911.13777884.488889253.3666672024-06-210.000.00125193.843265733.75025520.7
52024-06-21 03:00:00+00:0031.416588-17.130116-2.073.2000002.4211110.01006.86222212.43222281.688889229.8666672024-06-2129.8810.27126032.113402743.89326415.5
62024-06-21 04:00:00+00:0048.247879-27.732010-1.723.0777782.9544440.01006.90666713.76444474.344444241.9666672024-06-2129.8810.86126618.303512532.14427101.4
72024-06-21 05:00:00+00:0021.654301-39.054996-0.373.0333333.5233330.01006.92666714.77000067.155556252.6333332024-06-2130.5710.86127485.233660885.25927800.5
82024-06-21 06:00:00+00:0021.665791-42.032959-0.113.0555563.8322220.01007.12000015.62555661.322222277.9888892024-06-2129.8811.63128125.843797649.36228637.4
92024-06-21 07:00:00+00:0021.665791-40.926075-0.113.7222224.2788890.01007.27333316.18111157.777778282.9888892024-06-2123.829.80128566.333907126.15329399.8
datetimeUpDownspcloud_amountwind_speedprecipitation_amountpressureair_temperaturerelative_humiditywind_directiondateDown_CapUp_Capis_public_holidayelectricity_consumptionelectricity_consumption_Finnish_networkselectricity_consumption_forecast
39262024-12-01 13:00:00+00:0049.344997-8.2850004.848.0000004.7022220.0133331012.9600024.79444495.122222222.6888912024-12-0122.0010.14041689.906164151.51439481.8
39272024-12-01 14:00:00+00:0090.027504-16.4900004.737.9555564.7677780.0133331012.6555544.92000095.588889221.5666682024-12-0122.0010.14041873.506313550.05340313.1
39282024-12-01 15:00:00+00:0044.247501-16.2000013.487.9333334.9655560.0133331012.1755625.10222295.922222217.8111102024-12-018.1010.14041928.706366146.75640698.3
39292024-12-01 16:00:00+00:0039.365002-21.1999993.177.9555565.4088890.0200001011.6244515.34777896.111111219.1666682024-12-018.1010.00041949.606399452.93240663.1
39302024-12-01 17:00:00+00:0039.365002-24.0550003.568.0333336.0844440.0266671011.0700035.57555596.011112220.0333322024-12-018.109.62041355.906355390.77840479.6
39312024-12-01 18:00:00+00:0019.006666-17.1850012.938.0222226.2488890.0266671010.4344405.70000096.111111219.0777782024-12-018.1010.00040503.206176101.25839843.6
39322024-12-01 19:00:00+00:0033.200001-20.9375002.697.9111116.3902220.0133331010.1186655.73711196.020000219.7000002024-12-019.909.54039123.795818730.97238547.6
39332024-12-01 20:00:00+00:0033.993332-8.1200002.107.8555565.9933330.0133331009.7455575.83666795.966666217.5555572024-12-018.109.62039709.155914781.00338827.0
39342024-12-01 21:00:00+00:0069.455002-10.2000011.627.8666676.3217780.0133331009.2933356.00111195.044444214.9355562024-12-018.108.50038717.545733222.44738592.6
39352024-12-01 22:00:00+00:0038.910000-20.6300010.017.7333336.6511110.0200001008.8411136.10666793.966667214.1666662024-12-019.448.28037450.285423083.84037781.5